Fujitsu, Waseda University to co-operate on Digital Annealer Research in finance area
In the field of finance, the Digital Annealer has applications, such as the clustering method of analysis in predicting stock price changes.
New technologies that invade the financial services industry are becoming faster and more efficient. Today, Fujitsu Ltd (TYO:6702) announces that Fujitsu Laboratories and Waseda University have sealed a comprehensive collaborative activity agreement for joint research on the Digital Annealer.
Digital Annealer is a new technology that is used to solve large-scale combinatorial optimization problems instantly. It has a digital circuit design inspired by quantum phenomena, and can solve problems which are too difficult for classical computers to deal with.
The organizations have established the Fujitsu Co-Creation Research Laboratory at Waseda University, within Waseda’s Green Computing Systems Research Organization, as a joint research organizaiton to promote software development aimed at resolving real world combinatorial optimization problems using the Digital Annealer. The organization draws topics from Waseda University’s entire body of research, using the Digital Annealer to conduct research in a variety of fields, including finance, digital marketing, and logistics. Eventually, Fujitsu plans to incorporate the results of this joint research into its Digital Annealer business to contribute to practical social and economic advancements.
Fujitsu Laboratories and Waseda University have concluded a collaborative activity agreement uniting the two organizations’ research regarding software development. They have now established the Fujitsu Co-Creation Research Laboratory at Waseda University, fostering a shared understanding with regard to subjects such as research, development, and personnel training. Fujitsu and Waseda will move forward on joint research at the new laboratory in April 2019.
The joint research at the Fujitsu Co-Creation Research Laboratory will use the Digital Annealer to conduct joint studies in various applied fields, beginning with finance (predicting stock price changes), digital marketing (data analysis), and logistics (optimizing delivery).
In the field of finance, there are applications such as the clustering method of analysis in predicting stock price changes, which takes into account the feature value of numerical and text data in financial statements, used for credit ratings, as well as applications to arbitrage calculations for foreign exchange.In order to perform accurate calculations, however, there are many issues that need to be resolved, such as the need for further improvements in speed and accuracy for both the hardware and software.
In the field of digital marketing, there are high expectations for the creation of new data analysis methods to maximize the effect of marketing activities. For example, to make better suggestions based on information about customer activities, it is necessary to solve a combinatorial optimization problem consisting of numerous optimization parameters. Moreover, in order to present the customer with optimized information in real time, the problem has to be solved in just a few seconds.